EnviroLink

Team Name

Team 2428 - Hydro Hackers

Team Members

Project Description

Our project - EnviroLink fosters community engagement and collaboration by enabling real-time data collection across multiple locations in the Pine Rivers catchment and Moreton Bay, encouraging active participation and raising awareness of environmental changes.
This system provides Unity Water and The City of Moreton Bay with valuable insights into fluctuations in nitrogen and phosphorus levels throughout the waterways, supporting informed actions to protect our diverse flora and fauna. Generative AI will be utilised to supply the community with localised information related to water quality, flora, and fauna, empowering individuals with knowledge through gamification.
By harnessing the power of the community, we contribute to safeguarding local ecosystems as we grow our region, creating a sustainable and flourishing planet for generations to come.

Data Story

The EnviroLink App will be developed using a variety of local datasets to provide real-time insights and community engagement in protecting Moreton Bay’s ecosystems. The "Living with Local Wildlife" data from the City of Moreton Bay website will be used to share fun facts with the community through generative AI, making environmental education engaging. The Moreton Bay Ecosystems Plant Lists will be integrated to allow users to check scientific names of native plants using AI, helping suggest accurate names when reporting flora sightings.
A visual map will be created using the 2023 CMB 0.25m Contours dataset, allowing users to see data entry points within the app. Additionally, the ALA Species Sightings and OzAtlas (Atlas of Living Australia) databases will enable users to report new sightings of flora and fauna, increasing community involvement and contributing to a growing pool of real-time data.
The Ecosystem Health Monitoring Program dataset and Unitywater’s Mid-Field Monitoring Program dataset will map data collected by the community, allowing Unity Water and the City of Moreton Bay to take immediate action when issues arise, ensuring a more responsive approach to environmental management. This collaborative effort combines technology, data, and community engagement to protect the region’s biodiversity.
The Moreton Chatbot will leverage data from the Envirolink database by utilizing a combination of structured data retrieval and generative AI to provide users with relevant environmental facts. Here's how the process would work:

Data Access and Integration: The Envirolink database will contain structured environmental data, such as statistics, reports, or key facts about the Moreton Bay region's environment, including biodiversity, conservation efforts, pollution levels, and more. The chatbot will be integrated with this database, allowing it to query the information when users ask questions.

Query Processing: When a user asks the chatbot a question, the system will first use natural language processing (NLP) to interpret the query and extract the key intent or topic. For example, if a user asks, "What is the most common endangered species in Moreton Bay?" the chatbot will identify keywords like "endangered species" and "Moreton Bay."

Data Retrieval: Once the chatbot understands the user's question, it will query the Envirolink database for relevant data, such as endangered species information for the Moreton Bay region. This data will be in a structured format, typically containing facts, numbers, and categorical information.

Generative AI Response: After retrieving the data, the chatbot will use generative AI techniques to create a natural, conversational response. Instead of merely presenting raw data, the AI will craft a coherent and engaging answer that feels personalized. For instance, it might say, "In Moreton Bay, the Loggerhead Turtle is one of the most commonly found endangered species. Conservation efforts are in place to protect their nesting sites."

Adaptive Learning: Over time, the chatbot's AI will also learn from user interactions. If certain types of questions are frequently asked, it can adapt by refining its responses or highlighting the most relevant facts from the Envirolink database more efficiently.

This process ensures that the chatbot can share accurate and contextually relevant environmental facts with users in a conversational manner.